lgtm-mcp 1.0.1

LGTM Observability and Alertmanager MCP Server for Agentic AI!

Lgtm MCP

LGTM Stack (Alertmanager and Grafana) system observability orchestrator. Built with the highest architectural standards, incorporating dynamic facades, custom API routing, and FastMCP tool decoration.

Documentation — Installation, deployment, usage across the API and MCP interfaces, and guidance for provisioning the LGTM observability stack are maintained in the official documentation.

Table of Contents

• Overview
• Features
• Installation
• Usage
• Configuration
• MCP Tools
• Architecture
• Deployment
• Documentation
• Contributing
• License

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Overview

Lgtm MCP provides a high-performance, model-optimized interface to Lgtm capabilities. It isolates the model from underlying API transport complexity, ensuring safe, idempotent, and highly traceable system interactions.

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Features

• Dynamic Facade Orchestration: Integrates multi-inheritance clients cleanly under a single facade.
• Battle-Tested Resilience: Out-of-the-box credential authentication, connection polling, and request retry strategies.
• FastMCP Declarative Tools: Fast, native schema registration with full inline validation.
• Complete Test Intent Diversity: Deep, automated unit, integration, and mock tests ensuring high code coverage.

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⚙️ Dynamic Tool Selection & Visibility

This MCP server supports dynamic toolset selection and visibility filtering at runtime. This allows you to restrict the set of exposed tools in order to prevent blowing up the LLM's context window.

You can configure tool filtering via multiple input channels:

• CLI Arguments: Pass --tools or --toolsets (or their disabled counterparts --disabled-tools and --disabled-toolsets) during startup.
• Environment Variables: Define standard environment variables:
  • MCP_ENABLED_TOOLS / MCP_DISABLED_TOOLS
  • MCP_ENABLED_TAGS / MCP_DISABLED_TAGS
• HTTP SSE Request Headers: Pass custom headers during transport initialization:
  • x-mcp-enabled-tools / x-mcp-disabled-tools
  • x-mcp-enabled-tags / x-mcp-disabled-tags
• HTTP SSE Request Query Parameters: Append query parameters directly to your transport connection URL:
  • ?tools=tool1,tool2
  • ?tags=tag1

When query strings or parameters are supplied, an LLM-free Knowledge Graph resolution layer (using DynamicToolOrchestrator) matches query intents against known tool tags, names, or descriptions, with safe fallback and automated 24-hour background cache refreshing.

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Installation

Pick the extra that matches what you want to run:

Extra	Installs	Use when
lgtm-mcp[mcp]	Slim MCP server only (agent-utilities[mcp] — FastMCP/FastAPI)	You only run the MCP server (smallest install / image)
lgtm-mcp[agent]	Full agent runtime (agent-utilities[agent,logfire] — Pydantic AI + the epistemic-graph engine)	You run the integrated agent
lgtm-mcp[all]	Everything (mcp + agent + logfire)	Development / both surfaces

# MCP server only (recommended for tool hosting — slim deps)
uv pip install "lgtm-mcp[mcp]"

# Full agent runtime (Pydantic AI + epistemic-graph engine)
uv pip install "lgtm-mcp[agent]"

# Everything (development)
uv pip install "lgtm-mcp[all]"      # or: python -m pip install "lgtm-mcp[all]"

Container images (:mcp vs :agent)

One multi-stage docker/Dockerfile builds two right-sized images, selected by --target:

Image tag	Build target	Contents	Entrypoint
knucklessg1/lgtm-mcp:mcp	--target mcp	lgtm-mcp[mcp] — slim, no engine/pydantic-ai/dspy/llama-index/tree-sitter	lgtm-mcp
knucklessg1/lgtm-mcp:latest	--target agent (default)	lgtm-mcp[agent] — full agent runtime + epistemic-graph engine	lgtm-agent

docker build --target mcp   -t knucklessg1/lgtm-mcp:mcp    docker/   # slim MCP server
docker build --target agent -t knucklessg1/lgtm-mcp:latest docker/   # full agent

docker/mcp.compose.yml runs the slim :mcp server; docker/compose.yml runs the agent (:latest) with a co-located :mcp sidecar.

Knowledge-graph database (epistemic-graph)

The full agent ([agent] / :latest) embeds the epistemic-graph engine (pulled in transitively via agent-utilities[agent]). For production — or to share one knowledge graph across multiple agents — run epistemic-graph as its own database container and point the agent at it instead of embedding it. Deployment recipes (single-node + Raft HA), connection config, and the full database architecture (with diagrams) are documented in the epistemic-graph deployment guide. The slim [mcp] server does not require the database.

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Usage

You can launch the FastMCP server in stdio mode via Python module execution:

import asyncio
from lgtm_mcp.mcp_server import get_mcp_instance

async def main():
    mcp = get_mcp_instance()
    # Execute stdio loop or launch server
    print("MCP Server ready.")

if __name__ == "__main__":
    asyncio.run(main())

For direct shell launch, execute:

python -m lgtm_mcp.mcp_server

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Environment Variables

Package environment variables

Variable	Example	Description
ALERTMANAGER_URL	http://localhost:9093	Prometheus Alertmanager server API URL
GRAFANA_URL	http://localhost:3000	Grafana server API endpoint
LGTM_TOKEN	your_grafana_api_token	Grafana admin API Key or Service Token
LGTM_MCP_BASE_URL	http://localhost	Fallback base URL used when ALERTMANAGER_URL / GRAFANA_URL are unset
LGTM_MCP_USERNAME	—	Basic-auth username (alternative to LGTM_TOKEN)
LGTM_MCP_PASSWORD	—	Basic-auth password (alternative to LGTM_TOKEN)
LGTM_MCP_SSL_VERIFY	True	Verify TLS certificates on outbound API calls
ALERTMANAGERTOOL	True	MCP tools table (condensed action-routed surface).
GRAFANATOOL	True

Inherited agent-utilities variables (apply to every connector)

Variable	Example	Description
TRANSPORT	stdio	MCP transport: stdio
HOST	0.0.0.0	Bind host (HTTP transports)
PORT	8000	Bind port (HTTP transports)
MCP_TOOL_MODE	condensed	Tool surface: condensed
MCP_ENABLED_TOOLS	—	Comma-separated tool allow-list
MCP_DISABLED_TOOLS	—	Comma-separated tool deny-list
MCP_ENABLED_TAGS	—	Comma-separated tag allow-list
MCP_DISABLED_TAGS	—	Comma-separated tag deny-list
EUNOMIA_TYPE	none	Authorization mode: none
EUNOMIA_POLICY_FILE	mcp_policies.json	Embedded Eunomia policy file
EUNOMIA_REMOTE_URL	—	Remote Eunomia authorization server URL
ENABLE_OTEL	False	Enable OpenTelemetry export
OTEL_EXPORTER_OTLP_ENDPOINT	—	OTLP collector endpoint
MCP_CLIENT_AUTH	—	Outbound MCP auth (oidc-client-credentials for fleet calls)
OIDC_CLIENT_ID	—	OIDC client id (service-account auth)
OIDC_CLIENT_SECRET	—	OIDC client secret (service-account auth)
DEBUG	False	Verbose logging
PYTHONUNBUFFERED	1	Unbuffered stdout (recommended in containers)
MCP_URL	http://localhost:8000/mcp	URL of the MCP server the agent connects to
PROVIDER	openai	LLM provider for the agent
MODEL_ID	gpt-4o	Model id for the agent
ENABLE_WEB_UI	True	Serve the AG-UI web interface

9 package + 22 inherited variable(s). Auto-generated from .env.example + the shared agent-utilities set — do not edit.

Every variable the server reads. A local template is supplied inside .env.example — copy it to .env and fill in your endpoints/credentials.

Connection & Credentials

Variable	Description	Default
ALERTMANAGER_URL	Prometheus Alertmanager server API URL	http://localhost:9093
GRAFANA_URL	Grafana server API endpoint	http://localhost:3000
LGTM_TOKEN	Grafana admin API Key or Service Token	—

MCP server / transport

Variable	Description	Default
TRANSPORT	stdio, streamable-http, or sse	stdio
HOST	Bind host (HTTP transports)	0.0.0.0
PORT	Bind port (HTTP transports)	8000
MCP_TOOL_MODE	Tool surface: condensed, verbose, or both	condensed
MCP_ENABLED_TOOLS / MCP_DISABLED_TOOLS	Comma-separated tool allow/deny list	—
MCP_ENABLED_TAGS / MCP_DISABLED_TAGS	Comma-separated tag allow/deny list	—
DEBUG	Verbose logging	False
PYTHONUNBUFFERED	Unbuffered stdout (recommended in containers)	1

Tool toggles

Each action-routed tool can be disabled individually via its toggle env var (set to false). The full list is in the MCP Tools table above (ALERTMANAGERTOOL, GRAFANATOOL).

Agent CLI (full [agent] runtime only)

Variable	Description	Default
MCP_URL	URL of the MCP server the agent connects to	http://localhost:8000/mcp
PROVIDER	LLM provider (e.g. openai)	openai
MODEL_ID	Model id (e.g. gpt-4o)	gpt-4o
ENABLE_WEB_UI	Serve the AG-UI web interface	True

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MCP Tools

The following declarative FastMCP tools are registered and available to upstream AI agents:

Auto-generated — do not edit between the markers below.

Condensed action-routed tools (default — MCP_TOOL_MODE=condensed)

MCP Tool	Toggle Env Var	Description
lgtm_mcp_alertmanager	ALERTMANAGERTOOL	Manage LGTM MCP Alertmanager operations.
lgtm_mcp_grafana	GRAFANATOOL	Manage LGTM MCP Grafana operations.

Verbose 1:1 API-mapped tools (MCP_TOOL_MODE=verbose or both)

14 per-operation tools — one per public API method (click to expand)

MCP Tool	Toggle Env Var	Description
lgtm_create_alerts	APITOOL	Create new Alerts (Helper method matching post_alerts).
lgtm_create_dashboard	APITOOL	Create dashboard.
lgtm_create_silence	APITOOL	Silence active alerts (Helper method for backward compatibility).
lgtm_delete_silence	APITOOL	Delete silence rule.
lgtm_get_alert_groups	APITOOL	Get a list of alert groups.
lgtm_get_alerts	APITOOL	Get a list of alerts.
lgtm_get_dashboards	APITOOL	Get Grafana dashboards.
lgtm_get_receivers	APITOOL	Get list of all receivers (notification integrations).
lgtm_get_silence	APITOOL	Get a silence by its ID.
lgtm_get_silences	APITOOL	Get a list of silences.
lgtm_get_status	APITOOL	Get current status of an Alertmanager instance and its cluster.
lgtm_post_alerts	APITOOL	Create new Alerts.
lgtm_post_silences	APITOOL	Post a new silence or update an existing one.
lgtm_query_datasource	APITOOL	Query a datasource.

2 action-routed tool(s) (default) · 14 verbose 1:1 tool(s). Each is enabled unless its <DOMAIN>TOOL toggle is set false; MCP_TOOL_MODE selects the surface (condensed default · verbose 1:1 · both). Auto-generated — do not edit.

See docs/overview.md or docs/concepts.md for deeper operational examples.

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Architecture

This package uses the standardized Agent-Utilities dynamic facade architecture:

graph TD
    User([User Agent]) --> Server[FastMCP Server]
    Server --> Facade[Api Dynamic Facade]
    Facade --> ClientBase[ApiClientBase]
    Facade --> Auth[Credentials Auth Handler]
    ClientBase --> Service([External Service API])

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Deployment

Bare-Metal (Standard pip)

1. Set up your Python virtual environment (>= 3.10).
2. Install the package: pip install .[all]
3. Export credentials:

   export LGTM_URL="http://localhost:3000"
   

4. Run: python -m lgtm_mcp.mcp_server

Container (Docker Compose)

A standard compose structure is provided inside the docker/ folder. Build and deploy:

docker compose -f docker/compose.yml up --build -d

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Additional Deployment Options

lgtm-mcp can also run as a local container (Docker / Podman / uv) or be consumed from a remote deployment. The Deployment guide has full, copy-paste mcp_config.json for all four transports — stdio, streamable-http, local container / uv, and remote URL:

• Local container / uv — launch the server from mcp_config.json via uvx, docker run, or podman run, or point at a local streamable-http container by url.
• Remote URL — connect to a server deployed behind Caddy at http://lgtm-mcp.arpa/mcp using the "url" key.

Documentation

The complete documentation is published as the official documentation site and is the recommended reference for installation, deployment, and day-to-day operation.

Page	Contents
Installation	pip, source, extras, prebuilt Docker image
Deployment	run the MCP server, the agent server, Compose, Caddy + Technitium, env config
Usage	the MCP tools and the Api Python client
Backing Platform	deploy the LGTM observability stack with Docker
Overview	architecture and the dynamic facade
Concepts	concept registry (CONCEPT:LGTM-*)

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Contributing

Please audit all code changes against ecosystem guidelines in CONTRIBUTING.md if available, and run:

pre-commit run --all-files

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License

This project is licensed under the MIT License. See the LICENSE file for complete details.

Deploy with agent-os-genesis

This package can be provisioned for you — skill-guided — by the agent-os-genesis universal skill (its single-package deploy mode): it picks your install method, seeds secrets to OpenBao/Vault (or .env), trusts your enterprise CA, registers the MCP server, and verifies it — the same machinery that stands up the whole Agent OS, narrowed to just this package. Ask your agent to "deploy lgtm-mcp with agent-os-genesis".

Install mode	Command
Bare-metal, prod (PyPI)	uvx lgtm-mcp · or uv tool install lgtm-mcp
Bare-metal, dev (editable)	uv pip install -e ".[all]" · or pip install -e ".[all]"
Container, prod	deploy knucklessg1/lgtm-mcp:latest via docker-compose / swarm / podman / podman-compose / kubernetes
Container, dev (editable)	deploy docker/compose.dev.yml (source-mounted at /src; edits live on restart)

Secrets are read-existing + seeded via vault_sync — you are only prompted for what's missing.